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Leveraging a Data Strategy with Seeq® to Create the Optimal Biotherapeutic Development Process 1.0.0

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From Data to Direction.  Scientists and engineers at the R&D, pilot, and production scales need a new way to harness the power of the data gathered, a new way to drive innovation through an enhanced stata strategy that leverages Seeq®.  Crucial elements for enabling pharmaceutical process innovation include:

  • understanding the key physical situation of the process,
  • identifying the right process analytical technology to obtain the required data,
  • connecting disparate data sources, and
  • implementing data analysis and visualization applications that make it easy to analyze and make changes, to improve quality and quantity of medicines.

Companies often capture all the data they need to improve operations within their data historians and other databases.  However, creating insight from this information can be difficult, expensive, and time-consuming using traditional approaches or limited data analytics tools.  For example, it is important to ensure that your data management applications provide:

  • A strong connection with all data historian(s) and other important databases
  • Automatic indexing of the sensor names/tags in the historian to make them easy to search and access related data
  • A comprehensive connection to other data sources
  • Rapid visualization of the time-series data over a designated period of time
  • Streamlined future analysis in a way that also facilitates collaboration

With a facile data visualization strategy, the world looks different.  Imagine having the ability to easily search and interact with past and present time-series data in a "Google-like" fashion and collaborate in real-time.  Imagine being able to make business critical decisions with more confidence simply because you have the data in hand.

In this presentation, we focus on a specific case study example in upstream bioprocessing that illustrates how to drive innovations through an effective data strategy using Seeq®.

Using an enhanced data aggregation and visualization strategy, factors that affect product quality ca ben rapidly identified, thus further enabling definition of key performance indicators in early development.  Leveraging historical data allows small-scale model verification and insights into challenges of scale up.

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